J. Nathan Kutz, University of Washington, Seattle Washington, Steven L. Brunton, University of Washington, Seattle Washington, Bingni W. Brunton, University of Washington, Seattle Washington, Joshua L. Procor, Institute for Disease Modeling, Bellevue, Washington.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Philadelphia :
نام ناشر، پخش کننده و غيره
Society for Industrial and Applied Mathematics,
تاریخ نشرو بخش و غیره
[2016]
مشخصات ظاهری
نام خاص و کميت اثر
xvi, 234 pages :
ساير جزييات
illustrations (some color) ;
ابعاد
26 cm.
فروست
عنوان فروست
Other titles in applied mathematics ;
مشخصه جلد
149
یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references (pages 213-231) and index.
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Data-driven dynamical systems is a burgeoning fieldit connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.--